• 제목/요약/키워드: Prediction of Delay Time

검색결과 227건 처리시간 0.021초

Compensating time delay in semi-active control of a SDOF structure with MR damper using predictive control

  • Bathaei, Akbar;Zahrai, Seyed Mehdi
    • Structural Engineering and Mechanics
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    • 제82권4호
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    • pp.445-458
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    • 2022
  • Some of the control systems used in engineering structures that use sensors and decision systems have some time delay reducing efficiency of the control system or even might make it unstable. In this research, in addition to considering the effect of the time delay in vibration control process, predictive control is used to compensate the time delay. A semi-active vibration control approach with the help of magneto-rheological dampers is implemented. In addition to using fuzzy inference system to determine the appropriate control voltage for MR damper, structural behavior prediction system and specifying future responses are also used such that the time delays occurring within control process are overcome. For this purpose, determination of prediction horizon is conducted for one, five, and ten steps ahead for single degree of freedom structures with periods ranging from 0.1 to 4 seconds, subjected to twenty earthquake excitations. The amount of time delay applied to the control system is 0.1 seconds. The obtained results indicate that for 0.1 second time delay, average prediction error values compared to the case without time delay is 3.47 percent. Having 0.1 second time delay in a semi-active control system reduces its efficiency by 11.46 percent; while after providing the control system with structure behavior prediction, the difference in the results for the control system without time delay is just 1.35 percent on average; indicating a 10.11 percent performance improvement for the control system.

Analysis of delay compensation in real-time dynamic hybrid testing with large integration time-step

  • Zhu, Fei;Wang, Jin-Ting;Jin, Feng;Gui, Yao;Zhou, Meng-Xia
    • Smart Structures and Systems
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    • 제14권6호
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    • pp.1269-1289
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    • 2014
  • With the sub-stepping technique, the numerical analysis in real-time dynamic hybrid testing is split into the response analysis and signal generation tasks. Two target computers that operate in real-time may be assigned to implement these two tasks, respectively, for fully extending the simulation scale of the numerical substructure. In this case, the integration time-step of solving the dynamic response of the numerical substructure can be dozens of times bigger than the sampling time-step of the controller. The time delay between the real and desired feedback forces becomes more striking, which challenges the well-developed delay compensation methods in real-time dynamic hybrid testing. This paper focuses on displacement prediction and force correction for delay compensation in the real-time dynamic hybrid testing with a large integration time-step. A new displacement prediction scheme is proposed based on recently-developed explicit integration algorithms and compared with several commonly-used prediction procedures. The evaluation of its prediction accuracy is carried out theoretically, numerically and experimentally. Results indicate that the accuracy and effectiveness of the proposed prediction method are of significance.

스미스 예측기와 그레이 예측 방법을 적용한 시간 지연이 있는 비 가시 환경에서의 원격로봇제어 (Teleoperation by using Smith prediction and Grey prediction with a Time-delay in a Non-visible Environment)

  • 정재훈;김덕수;이장명
    • 로봇학회논문지
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    • 제11권4호
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    • pp.277-284
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    • 2016
  • A new prediction scheme has been proposed for the robust teleoperation in a non-visible environment. The positioning error caused by the time delay in the non-visible environment has been compensated for by the Smith predictor and the sensory data have been estimated by the Grey model. The Smith predictor is effective for the compensation of the positioning error caused by the time delay with a precise system model. Therefore the dynamic model of a mobile robot has been used in this research. To minimize the unstable and erroneous states caused by the time delay, the estimated sensor data have been sent to the operator. Through simulations, the possibility of compensating the errors caused by the time delay has been verified using the Smith predictor. Also the estimation reliability of the measurement data has been demonstrated. Robust teleoperations in a non-visible environment have been performed with a mobile robot to avoid the obstacles effective to go to the target position by the proposed prediction scheme which combines the Smith predictor and the Grey model. Even though the human operator is involved in the teleoperation loop, the compensation effects have been clearly demonstrated.

종속형 퍼지 뉴럴 네트워크를 이용한 네트워크 제어 시스템의 시간 지연 예측 (Time Delay Prediction of Networked Control Systems using Cascade Structures of Fuzzy Neural Networks)

  • 이철균;한창욱
    • 전기전자학회논문지
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    • 제23권3호
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    • pp.899-903
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    • 2019
  • 네트워크 제어 시스템에서는 송신 신호의 시간 변동 지연이 불가피하다. 전송 지연이 고정된 샘플링 시간보다 길면 시스템이 불안정해진다. 이 문제를 해결하기 위해 본 논문은 논리 기반의 퍼지 신경망을 이용하여 지연을 예측하는 방법을 제안하며, 예측된 시간 지연은 네트워크 제어 시스템의 샘플링 시간으로 사용된다. 제안된 방법의 효과를 검증하기 위해, 실제 시스템에서 수집된 지연 데이터를 사용하여 논리 기반 퍼지 신경 네트워크를 훈련하고 테스트한다.

Financial Data Mining Using Time delay Neural Networks

  • Kim, Hyun-Jung;Shin, Kyung-Shik
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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    • pp.122-127
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    • 2001
  • This study investigates the effectiveness of time delay neural networks(TDNN) for the time dependent prediction domain. Although it is well-known fact that the back-propagation neural network(BPN) performs well in pattern recognition tasks, the method has some limitations in that it can only learn an input mapping of static (or spatial) patterns that are independent of time of sequences. The preliminary results show that the accuracy of TDNN is higher than the standard BPN with time lag. Our proposed approaches are demonstrated by the stork market prediction domain.

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Effect of Dimension Reduction on Prediction Performance of Multivariate Nonlinear Time Series

  • Jeong, Jun-Yong;Kim, Jun-Seong;Jun, Chi-Hyuck
    • Industrial Engineering and Management Systems
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    • 제14권3호
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    • pp.312-317
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    • 2015
  • The dynamic system approach in time series has been used in many real problems. Based on Taken's embedding theorem, we can build the predictive function where input is the time delay coordinates vector which consists of the lagged values of the observed series and output is the future values of the observed series. Although the time delay coordinates vector from multivariate time series brings more information than the one from univariate time series, it can exhibit statistical redundancy which disturbs the performance of the prediction function. We apply dimension reduction techniques to solve this problem and analyze the effect of this approach for prediction. Our experiment uses delayed Lorenz series; least squares support vector regression approximates the predictive function. The result shows that linearly preserving projection improves the prediction performance.

Adaptive Input Traffic Prediction Scheme for Absolute and Proportional Delay Differentiated Services in Broadband Convergence Network

  • Paik, Jung-Hoon;Ryoo, Jeong-Dong;Joo, Bheom-Soon
    • ETRI Journal
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    • 제30권2호
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    • pp.227-237
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    • 2008
  • In this paper, an algorithm that provides absolute and proportional differentiation of packet delays is proposed with the objective of enhancing quality of service in future packet networks. It features an adaptive scheme that adjusts the target delay for every time slot to compensate the deviation from the target delay, which is caused by prediction error on the traffic to arrive at the next time slot. It predicts the traffic to arrive at the beginning of a time slot and measures the actual arrived traffic at the end of the time slot. The difference between them is utilized by the delay control operation for the next time slot to offset it. Because the proposed algorithm compensates the prediction error continuously, it shows superior adaptability to bursty traffic and exponential traffic. Through simulations we demonstrate that the algorithm meets the quantitative delay bounds and is robust to traffic fluctuation in comparison with the conventional non-adaptive mechanism. The algorithm is implemented with VHDL on a Xilinx Spartan XC3S1500 FPGA, and the performance is verified under the test board based on the XPC860P CPU.

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Internet Roundtrip Delay Prediction Using the Maximum Entropy Principle

  • Liu, Peter Xiaoping;Meng, Max Q-H;Gu, Jason
    • Journal of Communications and Networks
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    • 제5권1호
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    • pp.65-72
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    • 2003
  • Internet roundtrip delay/time (RTT) prediction plays an important role in detecting packet losses in reliable transport protocols for traditional web applications and determining proper transmission rates in many rate-based TCP-friendly protocols for Internet-based real-time applications. The widely adopted autoregressive and moving average (ARMA) model with fixed-parameters is shown to be insufficient for all scenarios due to its intrinsic limitation that it filters out all high-frequency components of RTT dynamics. In this paper, we introduce a novel parameter-varying RTT model for Internet roundtrip time prediction based on the information theory and the maximum entropy principle (MEP). Since the coefficients of the proposed RTT model are updated dynamically, the model is adaptive and it tracks RTT dynamics rapidly. The results of our experiments show that the MEP algorithm works better than the ARMA method in both RTT prediction and RTO estimation.

비선형 시계열 하천생태모형 개발과정 중 시간지연단계와 입력변수, 모형 예측성 간 관계평가 (Relationship among Degree of Time-delay, Input Variables, and Model Predictability in the Development Process of Non-linear Ecological Model in a River Ecosystem)

  • 정광석;김동균;윤주덕;라긍환;김현우;주기재
    • 생태와환경
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    • 제43권1호
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    • pp.161-167
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    • 2010
  • In this study, we implemented an experimental approach of ecological model development in order to emphasize the importance of input variable selection with respect to time-delayed arrangement between input and output variables. Time-series modeling requires relevant input variable selection for the prediction of a specific output variable (e.g. density of a species). Inadequate variable utility for input often causes increase of model construction time and low efficiency of developed model when applied to real world representation. Therefore, for future prediction, researchers have to decide number of time-delay (e.g. months, weeks or days; t-n) to predict a certain phenomenon at current time t. We prepared a total of 3,900 equation models produced by Time-Series Optimized Genetic Programming (TSOGP) algorithm, for the prediction of monthly averaged density of a potamic phytoplankton species Stephanodiscus hantzschii, considering future prediction from 0- (no future prediction) to 12-months ahead (interval by 1 month; 300 equations per each month-delay). From the investigation of model structure, input variable selectivity was obviously affected by the time-delay arrangement, and the model predictability was related with the type of input variables. From the results, we can conclude that, although Machine Learning (ML) algorithms which have popularly been used in Ecological Informatics (EI) provide high performance in future prediction of ecological entities, the efficiency of models would be lowered unless relevant input variables are selectively used.

제어 시지연이 있는 고성능 PI 전류제어기에 대한 예측전류의 적용방법 (A Novel Utilization Method of the Predicted Current in the High Performance PI Current Controller with a Control time delay)

  • 이진우
    • 전력전자학회논문지
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    • 제11권5호
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    • pp.426-430
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    • 2006
  • 본 논문에서는 제어 시지연을 갖는 고성능 PI 전류제어기에 대한 새로운 예측전류 적용방법을 모색한다. 먼저 선형 영구자석 동기전동기를 사용한 선형 서보 제어시스템에 존재하는 불가피한 전류예측 오차원인을 분석하고, 전류예측 오차와 제어 시지연을 고려한 전류제어 성능 개선 방법으로 수정된 동기좌표계 비간섭 PI 전류제어기를 제안한다. 그리고 시뮬레이션 및 실험 결과를 통하여 제안된 전류제어기가 서보 제어시스템에 존재하는 전류예측 오차와 제어 시지연이 있는 경우에도 개선된 전류제어응답을 보임을 검증하였다.